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import cv2
import time
from PIL import Image, ImageOps
import numpy as np
import streamlit as st
import tensorflow as tf
@st.cache(allow_output_mutation=True)
def load_model():
model=tf.keras.models.load_model('MN21.h5')
return model
with st.spinner('Model is being loaded..'):
model=load_model()
st.write("""# SaferNet with AI""")
file = st.file_uploader("Please upload an image to classify", type=["jpg", "png", "jpeg"])
def import_and_predict(image_data, model):
size = (224,224)
image = ImageOps.fit(image_data, size, Image.ANTIALIAS)
image = np.asarray(image)
img = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
#img_resize = (cv2.resize(img, dsize=(75, 75), interpolation=cv2.INTER_CUBIC))/255.
img_reshape = np.reshape(img,(1,224,224,3))
st.write(img_reshape.shape)
start = time.time()
prediction = model.predict(img_reshape)
end = time.time()
time_take = end - start
return prediction, time_take
if file is None:
st.text("Please upload an image file")
else:
image = Image.open(file)
st.image(image, use_column_width=True)
predictions, time_take = import_and_predict(image, model)
st.write("Time taken to predict is ", time_take, "second")
st.write(predictions)
st.write(predictions.shape)
st.write('0,0',predictions[0][0])
st.write('0,1',predictions[0][1])
if predictions[0][0] < 0.5:
st.write("This is SFW image :sunglasses:")
else:
st.write("This is NSFW image") |